Evidence map›Paper›PMID 27653774›Full record

ArticleEvaluation & the health professions2017

Improving Initiation and Tracking of Research Projects at an Academic Health Center: A Case Study.

Susanne Schmidt, Martin Goros, Helen M Parsons, Can Saygin, Hung-Da Wan, Paula K Shireman, Jonathan A L Gelfond

Open access · greenAbstract read
In one paragraph

Article in Evaluation & the health professions, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.4field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Susanne Schmidt1 The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Martin Goros1 The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Helen M Parsons1 The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Can Saygin2 The University of Texas at San Antonio, San Antonio, TX, USA.
Hung-Da Wan2 The University of Texas at San Antonio, San Antonio, TX, USA.
Paula K Shireman1 The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Jonathan A L Gelfond1 The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
The University of Texas Health Science Center at San Antonio · USThe University of Texas at San Antonio · US

Funding

Institute for Integration of Medicine & Science: A Partnership to Improve HealthUL1TR001120 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI CLARK, ROBERT A, HARGREAVES, KENNETH M · 2013 to 2017
$16.5M
San Antonio OAIC - Research Education Component (REC)P30AG044271 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Kelly Renee Reveles · 2015 to 2026
$14.1M
Institute for Integration of Medicine & Science: A Partnership to Improve HealthKL2TR001118 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI CLARK, ROBERT A, DOUGHERTY, DONALD M · 2013 to 2017
$3.4M
Institute for Integration of Medicine & Science: A Partnership to Improve HealthTL1TR001119 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI CLARK, ROBERT A, DOUGHERTY, DONALD M · 2013 to 2017
$640k
NCATS NIH HHS KL2 TR001118NCATS NIH HHS TL1 TR001119NCATS NIH HHS UL1 TR001120NIA NIH HHS P30 AG044271
6 · The paper itself

Abstract

Research service cores at academic health centers are important in driving translational advancements. Specifically, biostatistics and research design units provide services and training in data analytics, biostatistics, and study design. However, the increasing demand and complexity of assigning appropriate personnel to time-sensitive projects strains existing resources, potentially decreasing productivity and increasing costs. Improving processes for project initiation, assigning appropriate personnel, and tracking time-sensitive projects can eliminate bottlenecks and utilize resources more efficiently. In this case study, we describe our application of lean six sigma principles to our biostatistics unit to establish a systematic continual process improvement cycle for intake, allocation, and tracking of research design and data analysis projects. The define, measure, analyze, improve, and control methodology was used to guide the process improvement. Our goal was to assess and improve the efficiency and effectiveness of operations by objectively measuring outcomes, automating processes, and reducing bottlenecks. As a result, we developed a web-based dashboard application to capture, track, categorize, streamline, and automate project flow. Our workflow system resulted in improved transparency, efficiency, and workload allocation. Using the dashboard application, we reduced the average study intake time from 18 to 6 days, a 66.7% reduction over 12 months (January to December 2015).

Indexed as

Efficiency, OrganizationalAcademic Medical CentersHumansOrganizational Case StudiesQuality ImprovementTotal Quality ManagementWorkflowWorkloadacademic biostatistics unitslean six sigmaproject trackingR shinyweb-based dashboard

Identifiers

PMID27653774
PMCPMC5813810
OpenAlexW2521717238

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.